fiftyone.utils.tf.TFObjectDetectionSampleParser

class documentation

class TFObjectDetectionSampleParser(TFRecordSampleParser): (source)

Constructor: TFObjectDetectionSampleParser(force_rgb)

Parser for samples in TF Object Detection API format.

This implementation supports samples that are tf.train.Example protos whose features follow the format described in :ref:`this page <TFObjectDetectionDataset-import>`.

Parameters
force_rgb	whether to force convert all images to RGB

Method	`get_image_metadata`	Returns the image metadata for the current sample.
Property	`has_image_metadata`	Whether this parser produces `fiftyone.core.metadata.ImageMetadata` instances for samples that it parses.
Property	`has_image_path`	Whether this parser produces paths to images on disk for samples that it parses.
Property	`label_cls`	The `fiftyone.core.labels.Label` class(es) returned by this parser.
Method	`_parse_image`	Undocumented
Method	`_parse_image_metadata`	Undocumented
Method	`_parse_label`	Undocumented
Constant	`_FEATURES`	Undocumented

Inherited from TFRecordSampleParser:

Method	`__init__`	Undocumented
Method	`clear_sample`	Clears the current sample.
Method	`get_image`	Returns the image from the current sample.
Method	`get_label`	Returns the label for the current sample.
Method	`_parse_features`	Undocumented
Instance Variable	`_channels`	Undocumented
Instance Variable	`_current_features_cache`	Undocumented
Property	`_current_features`	Undocumented

Inherited from LabeledImageSampleParser (via TFRecordSampleParser):

Method get_image_path Returns the image path for the current sample.

Inherited from SampleParser (via TFRecordSampleParser, LabeledImageSampleParser):

Method	`with_sample`	Sets the current sample so that subsequent calls to methods of this parser will return information from the given sample.
Property	`current_sample`	The current sample.
Instance Variable	`_current_sample`	Undocumented

def get_image_metadata(self): (source) ¶

overrides fiftyone.utils.data.parsers.LabeledImageSampleParser.get_image_metadata

Returns the image metadata for the current sample.

Returns
a `fiftyone.core.metadata.ImageMetadata` instance

@property
has_image_metadata = (source) ¶

overrides fiftyone.utils.data.parsers.LabeledImageSampleParser.has_image_metadata

Whether this parser produces fiftyone.core.metadata.ImageMetadata instances for samples that it parses.

@property
has_image_path = (source) ¶

overrides fiftyone.utils.data.parsers.LabeledImageSampleParser.has_image_path

Whether this parser produces paths to images on disk for samples that it parses.

@property
label_cls = (source) ¶

overrides fiftyone.utils.data.parsers.LabeledImageSampleParser.label_cls

The fiftyone.core.labels.Label class(es) returned by this parser.

This can be any of the following:

a fiftyone.core.labels.Label class. In this case, the parser is guaranteed to return labels of this type
a list or tuple of fiftyone.core.labels.Label classes. In this case, the parser can produce a single label field of any of these types
a dict mapping keys to fiftyone.core.labels.Label classes. In this case, the parser will return label dictionaries with keys and value-types specified by this dictionary. Not all keys need be present in the imported labels
None. In this case, the parser makes no guarantees about the labels that it may return

def _parse_image(self, features): (source) ¶

overrides fiftyone.utils.tf.TFRecordSampleParser._parse_image

Undocumented

def _parse_image_metadata(self, features): (source) ¶

Undocumented

def _parse_label(self, features): (source) ¶

overrides fiftyone.utils.tf.TFRecordSampleParser._parse_label

Undocumented

_FEATURES = (source) ¶

overrides fiftyone.utils.tf.TFRecordSampleParser._FEATURES

Undocumented

Value

{'image/height': tf.io.FixedLenFeature([], tf.int64),
 'image/width': tf.io.FixedLenFeature([], tf.int64),
 'image/filename': tf.io.FixedLenFeature([], tf.string),
 'image/source_id': tf.io.FixedLenFeature([], tf.string),
 'image/encoded': tf.io.FixedLenFeature([], tf.string),
 'image/format': tf.io.FixedLenFeature([], tf.string),
 'image/object/bbox/xmin': tf.io.FixedLenSequenceFeature([], tf.float32,
...